| 224 |
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies |
2004 |
SIGMOD |
0.00032743209 |
| 325 |
The History of Histograms (abridged) |
2003 |
VLDB |
0.00027398081 |
| 430 |
Approximate Query Processing: Taming the TeraBytes! A Tutorial |
2001 |
VLDB |
0.00023406426 |
| 477 |
Model-Driven Data Acquisition in Sensor Networks |
2004 |
VLDB |
0.00022205608 |
| 491 |
Query by Output |
2009 |
SIGMOD |
0.00021960753 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 680 |
Towards a Robust Query Optimizer: A Principled and Practical Approach |
2005 |
SIGMOD |
0.00018193263 |
| 709 |
A Case for A Collaborative Query Management System |
2009 |
CIDR |
0.00017740603 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 905 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423174 |
| 915 |
On Schema Matching with Opaque Column Names and Data Values |
2003 |
SIGMOD |
0.00015362622 |
| 1,082 |
A Formal Analysis of Information Disclosure in Data Exchange |
2004 |
SIGMOD |
0.00014196516 |
| 1,239 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013091459 |
| 1,536 |
Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions |
2011 |
VLDB |
0.00011458359 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011050093 |
| 1,685 |
Fast Computation of Database Operations using Graphics Processors |
2004 |
SIGMOD |
0.0001090924 |
| 1,699 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010848882 |
| 1,727 |
QuickSel: Quick Selectivity Learning with Mixture Models |
2020 |
SIGMOD |
0.00010731889 |
| 1,756 |
Sampling-Based Query Re-Optimization |
2016 |
SIGMOD |
0.00010659753 |
| 1,972 |
Approximate Lineage for Probabilistic Databases |
2008 |
VLDB |
9.8937766e-05 |
| 2,120 |
Using Probabilistic Models for Data Management in Acquisitional Environments |
2005 |
CIDR |
9.5017579e-05 |
| 2,136 |
SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads |
2003 |
VLDB |
9.4668797e-05 |
| 2,295 |
Data Generation using Declarative Constraints |
2011 |
SIGMOD |
9.0842571e-05 |
| 2,359 |
Consistently Estimating the Selectivity of Conjuncts of Predicates |
2005 |
VLDB |
8.967267e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.955077e-05 |
| 2,551 |
GORDIAN: Efficient and Scalable Discovery of Composite Keys |
2006 |
VLDB |
8.5553153e-05 |
| 2,769 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1512848e-05 |
| 2,781 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1282042e-05 |
| 2,971 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
7.7935535e-05 |
| 3,402 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.134261e-05 |
| 3,455 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0760196e-05 |
| 3,516 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.018912e-05 |
| 3,597 |
Graph-Based Synopses for Relational Selectivity Estimation |
2006 |
SIGMOD |
6.9337747e-05 |
| 3,656 |
Conditional Selectivity for Statistics on Query Expressions |
2004 |
SIGMOD |
6.8712579e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6227223e-05 |
| 3,955 |
Efficiently Approximating Selectivity Functions using Low Overhead Regression Models |
2020 |
VLDB |
6.5895015e-05 |
| 3,992 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5519369e-05 |
| 4,352 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
6.2542257e-05 |
| 4,372 |
Sample Debiasing in the Themis Open World Database System |
2020 |
SIGMOD |
6.2367043e-05 |
| 4,413 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
6.1989918e-05 |
| 4,431 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.1870601e-05 |
| 4,890 |
Content-Based Routing: Different Plans for Different Data |
2005 |
VLDB |
5.8477169e-05 |
| 5,405 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
5.5243727e-05 |
| 5,528 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
5.4571136e-05 |
| 5,944 |
SAM: Database Generation from Query Workloads with Supervised Autoregressive Models |
2022 |
SIGMOD |
5.2583712e-05 |
| 5,983 |
Understanding Cardinality Estimation using Entropy Maximization |
2010 |
PODS |
5.240797e-05 |
| 6,365 |
Pre-training Summarization Models of Structured Datasets for Cardinality Estimation |
2022 |
VLDB |
5.0892829e-05 |
| 6,715 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
4.9464666e-05 |
| 6,837 |
Capturing Data Uncertainty in High-Volume Stream Processing |
2009 |
CIDR |
4.9063121e-05 |
| 7,854 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
4.6306186e-05 |